ArticleFrontiers in pediatrics2025
Development and validation of a non-invasive prediction model for identifying high-risk children with metabolic dysfunction-associated fatty liver disease.
Article in Frontiers in pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: This study aims to investigate the prevalence and risk factors of Metabolic dysfunction-associated fatty liver disease (MAFLD) in pediatric populations and establish a novel health index scoring system derived from key risk parameters for early identification of high-risk children with MAFLD. Method: In this cross-sectional study, a systematic random sampling method was employed to recruit children (6-18 years) with MAFLD. Data collection involved standardized questionnaires and comprehensive anthropometric measurements. The prevalence of MAFLD was determined through epidemiological analysis. Both univariate and multivariate logistic regression models were systematically applied to identify independent risk factors ( Results: The study cohort comprised 2,190 pediatric participants, revealing an overall MAFLD prevalence of 26.30%. Significant demographic disparities were observed: males exhibited a higher prevalence than females. The age, BMI (Body Mass Index), Waist-Hip Ratio (WHR), and Waist-Height Ratio (WHtR) values of the MAFLD group were higher than those of the Non-MAFLD group, and the difference was statistically significant. Multivariable logistic regression subsequently identified seven independent predictors ( Conclusion: This study establishes seven independent determinants of MAFLD in pediatric populations: age, gender, BMI, waist-hip ratio, waist-height ratio, sleep duration, and frequent dessert consumption (
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